Results 181 to 190 of about 7,286,935 (343)

Characterizing the salivary RNA landscape to identify potential diagnostic, prognostic, and follow‐up biomarkers for breast cancer

Molecular Oncology, EarlyView.
This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan, Irina Primac, Emre Etlioglu, Laurens Debruyne, Ann Janssen, Magy Sallam, Kevin Tabury, Roel Quintens, Wiebren Tjalma, Mohammed Abderrafi Benotmane   +9 more
wiley   +1 more source

A Hybrid Approach to Model Reduction of Generalized Langevin Dynamics. [PDF]

J Stat Phys
Colangeli M, Duong MH, Muntean A.
europepmc   +1 more source

High Order Invariant Manifold Model Reduction for Systems with Non-Polynomial Non-Linearities: Geometrically Exact Finite Element Structures and Validity Limit

Aurélien Grolet, Alessandra Vizzaccaro, Marielle Debeurre, Olivier Thomas   +3 more
openalex   +1 more source

Guidance driven motion artifact reduction based on diffusion model [PDF]

Yuandong Liu, Ronghao Xu
openalex   +1 more source

Bridging the gap: Multi‐stakeholder perspectives of molecular diagnostics in oncology

Molecular Oncology, EarlyView.
Although molecular diagnostics is transforming cancer care, implementing novel technologies remains challenging. This study identifies unmet needs and technology requirements through a two‐step stakeholder involvement. Liquid biopsies for monitoring applications and predictive biomarker testing emerge as key unmet needs. Technology requirements vary by
Jorine Arnouts, Senada Koljenović, Elise Daems, Karolien De Wael, Marc Peeters, Léon C. van Kempen, Greetje Vanhoutte, Karen Zwaenepoel, Timon Vandamme   +8 more
wiley   +1 more source

Physics-informed machine learning for automatic model reduction in chemical reaction networks. [PDF]

Sci Rep
Pateras J, Zhang C, Majumdar S, Pal A, Ghosh P.   +4 more
europepmc   +1 more source

Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic. [PDF]

Biology (Basel), 2020
Bakhta A, Boiveau T, Maday Y, Mula O.
europepmc   +1 more source

Adenosine‐to‐inosine editing of miR‐200b‐3p is associated with the progression of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
A‐to‐I editing of miRNAs, particularly miR‐200b‐3p, contributes to HGSOC progression by enhancing cancer cell proliferation, migration and 3D growth. The edited form is linked to poorer patient survival and the identification of novel molecular targets.
Magdalena Niemira, Anna Skwarska, Karolina Chwialkowska, Agnieszka Ostrowska, Gabriela Sokolowska, Anna Zeller, Anna Erol, Andrzej Eljaszewicz, Bartosz Hanczaruk, Anna Michalska‐Falkowska, Agnieszka Tarasik, Joanna Reszec‐Gielazyn, Pawel Knapp, Marcin Moniuszko, Adam Kretowski   +14 more
wiley   +1 more source

Achieving Occam's razor: Deep learning for optimal model reduction. [PDF]

PLoS Comput Biol
Antal BB, Chesebro AG, Strey HH, Mujica-Parodi LR, Weistuch C.   +4 more
europepmc   +1 more source

Parallel Tempering with Lasso for model reduction in systems biology. [PDF]

PLoS Comput Biol, 2020
Gupta S, Lee REC, Faeder JR.
europepmc   +1 more source